Purpose The smart building concept has gained prominence in the construction sector during the past decade. In the United Arab Emirates, although smart building technology has been widely adopted in different building sectors, no empirical studies have examined the applicability of the smart buildings concept in prison facilities. The current study aims to understand the current status of prison buildings in the UAE and the challenges faced by the prison industry to implement new smart technology. Design/methodology/approach This study involved a semi-structured interview consisting of 14 participants who were interviewed face-to-face about their opinion about the objectives of the study. The interviewees were experts from the prison and construction industry of the UAE working at the top management level. Mind-maps were created from the thematic data using Nvivo software. Findings The results demonstrated that among current issues prevailing in prisons, overcrowding was regarded as the most severe issue. Additionally, in most cases, there is no systemic classification of inmates. Concerning the potential challenges in the implementation of smart technologies in the prison buildings, being too old and outdated of prison buildings are a significant concern, followed by a substantial gap in the approval system of budget to purchase new smart technology. Originality/value The findings of this study are of vital importance and help to identify potential challenges involved in the implementation of smart technologies in prison buildings that should be taken into consideration before selecting any new smart technology.

The selection of an appropriate smart building technology has been a challenge for stakeholders, because no specific selection criteria are currently available. This study aimed to identify the potential selection criteria for the selection of smart building technologies for prison buildings in the United Arab Emirates. A questionnaire survey was conducted to evaluate the relative importance of smart building technologies and the specific selection criteria. 238 experts from the public and the private sector with rich experience in the construction and prison industry participated in the survey. The data obtained were analyzed for descriptive statistics and the Mann-Whitney U test was conducted to compare the responses of the government and private sector respondents. Cronbach’s coefficient was estimated using reliability analysis. Finally, exploratory factor analysis was performed by Principal Axis Factoring (PAF) to extract the contributing factors and was further improved by varimax rotation using SPSS. To evaluate the appropriateness of the factor extraction, the Kaiser-Mayer-Olkin (KMO) measure of sampling accuracy and Barlett’s test of sphericity were conducted. The results demonstrated that most participants thought that the safety and security, anti-hacking capability, high working efficiency, and durability of the new smart building technology were very important. 14 listed selection criteria were extracted into three factors by factor analysis explaining 50.585% total variation. Regarding smart building technologies, fire protection was mostly voted by the participants followed by video surveillance and heat, ventilation, and air-conditioning system (HVAC). This study is a novel research study identifying the key selection criteria for the selection of important smart building technologies and would be helpful for a broad audience.

Prisons are the structures used for incarcerated inmates and are often overcrowded and understaffed. This often leads to inhumane conditions and increased violence. Smart building technologies can help to alleviate these problems to some extent and improve communication between staff and prisoners. However, selecting appropriate smart building technology for prison building requires significant effort, knowledge, and experience. The current study aims to develop a decision-making model for selecting smart building technologies for UAE prisons following the analytical hierarchy process (AHP) and fuzzy-TOPSIS. The results of AHP revealed that for the main criteria, economical criteria were the highest ranked with a global weight of 0.228, followed by technology and engineering criteria (global weights of 0.203 and 0.200, respectively). For sub-criteria, prison category and security was the highest ranked criterion with a global weight of 0.082 followed by antihacking capability (0.075). Concerning the final ranking of smart building technologies by fuzzy-TOPSIS, the safety and security system was the highest-ranked technology (Ci = 0.970), followed by the fire protection system (Ci = 0.636) and information and communication information network system (Ci = 0.605). To conclude, the current findings will assist UAE policymakers and prison authorities to select the most appropriate smart building technologies for UAE prison buildings.